Image Textures and Gibbs Random Fields
By: by Georgy L. Gimel'farb
Series: Computational Imaging and Vision -- 16; Computational Imaging and Vision -- 16
Publisher: Springer Netherlands
Published: 1999
Place of publication: Dordrecht
Language: eng
Format: [electronic resource] /
Number of pages: 251
ISBN-13: 9789401059121; 9789401144612
Subjects: Distribution (Probability theory); Data structures (Computer science); Computer vision; Artificial intelligence; Computer science
Description: This book presents novel techniques for describing image textures. Contrary to the usual practice of embedding the images to known modelling frameworks borrowed from statistical physics or other domains, this book deduces the Gibbs models from basic image features and tailors the modelling framework to the images. This approach results in more general Gibbs models than can be either Markovian or non-Markovian and possess arbitrary interaction structures and strengths. The book presents computationally feasible algorithms for parameter estimation and image simulation and demonstrates their abilities and limitations by numerous experimental results. The book avoids too abstract mathematical constructions and gives explicit image-based explanations of all the notions involved. Audience: The book can be read by both specialists and graduate students in computer science and electrical engineering who take an interest in texture analysis and synthesis. Also, the book may be interesting to specialists and graduate students in applied mathematics who explore random fields.
Notes: Online full text is restricted to subscribers.

Also available in print.

Mode of access: World Wide Web.